Detection and quantification of flow consistency in business process models

Area of Science:

• Information Systems
• Human-Computer Interaction
• Software Engineering

Background:

• Business process models (BPMs) visually represent complex processes.
• Model layout, determined by designers, may influence model usability.
• The impact of BPM layout on user perception is not well understood.

Purpose of the Study:

• To empirically identify key visual features of BPMs meaningful to users.
• To quantify these features into computational metrics for BPM analysis.
• To evaluate metrics for flow direction consistency in BPMs.

Main Methods:

• Proposed a set of measurable key visual features for BPM layout.
• Developed three distinct computational metrics for flow direction consistency.
• Conducted an empirical evaluation to compare metric effectiveness against human perception.
• Performed automatic evaluations for metric performance and computational capabilities.

Main Results:

• Identified specific visual features of BPMs that significantly influence user perception.
• Proposed and validated computational metrics for quantifying layout properties like flow consistency.
• Determined which proposed metric most effectively predicts human judgment of flow consistency.
• Demonstrated the performance and computational efficiency of the developed metrics.

Conclusions:

• The study provides a foundation for systematically analyzing the impact of BPM layout.
• Quantifiable metrics can objectively assess user-perceived visual features in BPMs.
• The developed metrics offer practical tools for improving BPM design and usability.